Dear R community, I am a PhD student at the University of Münster writing my thesis in psycholinguistics.
I am currently running statistical analysis on a dataset with 3 fixed factors (syntax, position), each with 2 levels and their interaction (syntax*position). The accuracy rate is the dependent variable. I first created a general linear mixed effects model (lme4), including both the factors and their interaction and requested its summary. *M1 = glmer (correctness ~ syntax+position + syntax*position +(1|subj_nr) + (1|item_sf), data = df.rus2, family = binomial) * I now want to test the contribution of the factors to the power of the model, taken separately, by creating further models with individual factors dropped and comparing the models to the baseline model. My question is: should I drop the factors from the original model? e.g. for the effect of syntax *M2 = glmer (correctness ~ syntax + syntax*position +(1|subj_nr) + (1|item_sf), data = df.rus2, family = binomial) * Or should I test the main effects separately from the interaction? The baseline model: *M0 = glmer (correctness ~ syntax + position +(1|subj_nr) + (1|item_sf), data = df.rus2, family = binomial)* Models for comparison: *M1 = glmer (correctness ~ syntax +(1|subj_nr) + (1|item_sf), data = df.rus2, family = binomial)* *M2 = glmer (correctness ~ position +(1|subj_nr) + (1|item_sf), data = df.rus2, family = binomial)* *M3 = glmer (correctness ~ syntax * position +(1|subj_nr) + (1|item_sf), data = df.rus2, family = binomial)* Thank you in advance. Sincerely Julia Edeleva [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list -- To UNSUBSCRIBE and more, see https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.